Alternatives to Solix EDMS

Satori is a Data Security Platform (DSP) that enables self-service data and analytics for data-driven companies. With Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. That means your data consumers get data access in seconds instead of weeks. Satori’s DSP dynamically applies the appropriate security and access policies, reducing manual data engineering work. Satori’s DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously classifies sensitive data in all your data stores (databases, data lakes, and data warehouses), and dynamically tracks data usage while applying relevant security policies. Satori enables your data use to scale across the company while meeting all data security and compliance requirements.

IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™. Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data: * profiling and classification * searching and risk-scoring * integration and federation * migration and replication * cleansing and enrichment * validation and unification * masking and encryption * reporting and wrangling * subsetting and testing Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.

Mask, generate, subset, virtualize, and automate your test data with the DATPROF Test Data Management Suite. Our solution helps managing Personally Identifiable Information and/or too large databases. Long waiting times for test data refreshes are a thing of the past.

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.

Testing and managing test data for IBM i, IBM iSeries, and AS/400 systems requires thorough validation of complex applications, extending down to the underlying data. TestBench for IBM i offers a robust and reliable solution for test data management, verification, and unit testing, seamlessly integrating with other tools to ensure overall application quality. Instead of duplicating the entire live database, you can focus on the specific data that is essential for your testing needs. By selecting or sampling data while maintaining complete referential integrity, you can streamline the testing process. You can easily identify which fields require protection and employ various obfuscation techniques to safeguard your data effectively. Additionally, you can monitor every insert, update, and delete action, including the intermediate states of the data. Setting up automatic alerts for data failures through customizable rules can significantly reduce manual oversight. This approach eliminates the tedious save and restore processes and helps clarify any inconsistencies in test results that stem from inadequate initial data. While comparing outputs is a reliable way to validate test results, it often involves considerable effort and is susceptible to mistakes; however, this innovative solution can significantly reduce the time spent on testing, making the entire process more efficient. With TestBench, you can enhance your testing accuracy and save valuable resources.

K2View believes that every enterprise should be able to leverage its data to become as disruptive and agile as possible. We enable this through our Data Product Platform, which creates and manages a trusted dataset for every business entity – on demand, in real time. The dataset is always in sync with its sources, adapts to changes on the fly, and is instantly accessible to any authorized data consumer. We fuel operational use cases, including customer 360, data masking, test data management, data migration, and legacy application modernization – to deliver business outcomes at half the time and cost of other alternatives.

Data management software is predominantly utilized by enterprise business teams, necessitating a design that prioritizes user-friendliness, automation, and intelligence. Furthermore, it is essential for the software to comply with a variety of industry-specific regulations and data protection mandates. To ensure that business teams can make informed, data-driven strategic decisions, the data must maintain standards of adequacy, accuracy, consistency, high quality, and secure accessibility. The software promotes an integrated methodology for managing data privacy, ensuring data quality, overseeing test data management, facilitating data analytics, and supporting data modeling. Additionally, it effectively manages escalating data volumes through a service engine-based architecture, while also addressing specialized data processing needs beyond standard functionalities via a user-defined function framework and Python adapter. Moreover, it establishes a streamlined governance framework that focuses on data privacy and quality management, enhancing overall data integrity. As a result, organizations can confidently rely on this software to support their evolving data requirements.

Effectively managing data throughout its lifecycle enables organizations to better achieve their business objectives while minimizing potential risks. It is essential to archive data from obsolete applications and past transaction records, ensuring that access remains available for compliance-related queries and reporting. By scaling data across various applications, databases, operating systems, and hardware platforms, organizations can enhance the security of their testing environments, speed up release cycles, and lower costs. Without proper data archiving, the performance of critical enterprise systems can suffer significantly. Addressing data growth directly at the source not only boosts efficiency but also reduces the risks tied to managing structured data over time. Additionally, safeguarding unstructured data within testing, development, and analytics environments across the organization is crucial for maintaining operational integrity. Ultimately, the absence of a robust data archiving strategy can hinder the effectiveness of vital business systems. Taking proactive steps to manage data effectively is key to fostering a more agile and resilient enterprise.

IRI DarkShield uses several search techniques to find, and multiple data masking functions to de-identify, sensitive data in semi- and unstructured data sources enterprise-wide. You can use the search results to provide, remove, or fix PII simultaneously or separately to comply with GDPR data portability and erasure provisions. DarkShield jobs are configured, logged, and run from IRI Workbench or a restful RPC (web services) API to encrypt, redact, blur, etc., the PII it discovers in: * NoSQL & RDBs * PDFs * Parquet * JSON, XML & CSV * Excel & Word * BMP, DICOM, GIF, JPG & TIFF using pattern or dictionary matches, fuzzy search, named entity recognition, path filters, or image area bounding boxes. DarkShield search data can display in its own interactive dashboard, or in SIEM software analytic and visualization platforms like Datadog or Splunk ES. A Splunk Adaptive Response Framework or Phantom Playbook can also act on it. IRI DarkShield is a breakthrough in unstructured data hiding technology, speed, usability and affordability. DarkShield consolidates, multi-threads, the search, extraction and remediation of PII in multiple formats and folders on your network and in the cloud, on Windows, Linux, and macOS.

As enterprise data explodes and is scattered across multiple systems, the oversight of privacy, data security and governance has become a very difficult task. Businesses are exposed to significant risks, including data breaches, privacy suits, and penalties. It takes months to find data privacy risks within an organization. A team of data engineers is involved in the effort. Data breaches and privacy legislation are forcing companies to better understand who has access to data and how it is used. Enterprise data is complex. Even if a team works for months to isolate data privacy risks, they may not be able to quickly find ways to reduce them.

Thales has revolutionized the landscape of data security with its CipherTrust Data Security Platform, which simplifies data protection, hastens compliance processes, and facilitates safe cloud transitions. This state-of-the-art platform employs a modern micro-services architecture that is optimized for cloud environments and incorporates essential features such as Data Discovery and Classification, seamlessly integrating the most effective functionalities from the Vormetric Data Security Platform along with KeySecure and its associated connector products. By merging data discovery, classification, safeguarding, and advanced access control with centralized key management, the CipherTrust Data Security Platform operates as a cohesive unit. Consequently, organizations experience a decrease in the resources needed for data security tasks, enhanced compliance measures, and a marked reduction in overall business risk. Acting as a comprehensive suite of data-centric security solutions, the CipherTrust Data Security Platform empowers businesses to effectively manage and control their data security needs from a single, unified interface, ensuring robust protection and compliance in a rapidly evolving digital landscape.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

Don't allow concerns about data security or privacy to obstruct your innovation efforts driven by analytics. Dataguise offers robust protection for personal and sensitive information through adaptable masking and encryption solutions, ensuring you can maximize business value. With data sets prepared for analysis delivered in near real-time, you can gain fresher insights and make informed decisions based on a complete understanding of your data landscape. Recognizing the diverse and evolving needs of our customers, Dataguise has built a strong network of carefully selected partners to provide more comprehensive solutions, services, and expertise. This executive guide illustrates how to safeguard data privacy while enhancing data value. When looking at various data discovery solutions, it's clear that Dataguise has a longer history, accommodates a wider array of data types and repositories, achieves lower false-positive rates, and consistently scans data at scale more effectively. By choosing Dataguise, organizations can confidently harness their data to drive decisions that best serve their business objectives, ultimately fostering a culture of informed and strategic decision-making.

The EMS Data Generator for MySQL is a remarkable application designed to create test data for MySQL database tables, offering options to save and modify scripts. This versatile utility enables users to replicate a production-like database environment, facilitating the simultaneous filling of multiple MySQL tables with test data. Users can specify which tables and columns to target for data generation, establish ranges of values, and create MySQL character fields based on specific patterns. Additionally, it allows for the input of custom value lists or the selection of values through SQL queries, along with tailored generation parameters for each type of field. With its diverse features, the tool simplifies the process of generating MySQL test data effectively. Furthermore, the Data Generator for MySQL includes a user-friendly console application, enabling one-click generation of test data using pre-defined templates. This added functionality streamlines workflows and enhances productivity for database developers.

Safeguard your data comprehensively with a robust, enterprise-level security solution that spans multicloud, hybrid, and on-premises environments, accommodating all types of data. Enhance security measures across diverse platforms while seamlessly discovering and categorizing structured, semi-structured, and unstructured data. Assess and prioritize data risks by considering both incident context and the potential for additional capabilities. Streamline data management through a unified service or dashboard that centralizes oversight. Guard against unauthorized data exposure and prevent breaches effectively. Make data-centric security, compliance, and governance processes simpler and more efficient. Create a consolidated perspective to glean insights on vulnerable data and users, while actively managing a Zero Trust framework and enforcing relevant policies. Leverage automation and workflows to save both time and resources, and ensure support for a wide range of file shares and data repositories, including those in public, private, data center, and third-party cloud environments. Address not only your current requirements but also future integrations as you evolve and expand cloud use cases, thereby enhancing your overall data security strategy. By implementing these measures, you can significantly bolster your organization’s resilience against data-related threats.

Gretel provides privacy engineering solutions through APIs that enable you to synthesize and transform data within minutes. By utilizing these tools, you can foster trust with your users and the broader community. With Gretel's APIs, you can quickly create anonymized or synthetic datasets, allowing you to handle data safely while maintaining privacy. As development speeds increase, the demand for rapid data access becomes essential. Gretel is at the forefront of enhancing data access with privacy-focused tools that eliminate obstacles and support Machine Learning and AI initiatives. You can maintain control over your data by deploying Gretel containers within your own infrastructure or effortlessly scale to the cloud using Gretel Cloud runners in just seconds. Leveraging our cloud GPUs significantly simplifies the process for developers to train and produce synthetic data. Workloads can be scaled automatically without the need for infrastructure setup or management, fostering a more efficient workflow. Additionally, you can invite your team members to collaborate on cloud-based projects and facilitate data sharing across different teams, further enhancing productivity and innovation.

Protecting your personal information is crucial, and it’s essential to create data that appears genuine for software development purposes. To achieve this, DOT Anonymizer provides a solution that effectively masks your testing data while maintaining its consistency across various data sources and database management systems. The risk of data breaches arises significantly when using personal or identifiable information in non-production environments such as development, testing, training, and business intelligence. With the growing number of regulations worldwide, organizations are increasingly required to anonymize or pseudonymize sensitive information. This process allows you to keep the original format of the data while your teams can operate with believable yet fictional datasets. It is vital to manage all your data sources effectively to ensure their continued utility. You can easily invoke DOT Anonymizer functions directly from your applications, ensuring consistent anonymization across all database management systems and platforms. Additionally, it’s important to maintain relationships between tables to guarantee that the data remains realistic. The tool is capable of anonymizing a variety of database types and file formats, including CSV, XML, JSON, and more. As the demand for data protection grows, utilizing a solution like DOT Anonymizer becomes increasingly essential for maintaining the integrity and confidentiality of your data.

Safeguard your file and database information from potential abuse while ensuring compliance with both industry standards and governmental regulations by utilizing this comprehensive suite of integrated encryption solutions. IBM Guardium Data Encryption offers a cohesive set of products that share a unified infrastructure. These scalable solutions incorporate encryption, tokenization, data masking, and key management features, essential for protecting and regulating access to databases, files, and containers across hybrid multicloud environments, thereby securing assets located in cloud, virtual, big data, and on-premises settings. By effectively encrypting file and database data through functionalities like tokenization, data masking, and key rotation, organizations can successfully navigate compliance with various regulations, including GDPR, CCPA, PCI DSS, and HIPAA. Moreover, the extensive capabilities of Guardium Data Encryption—including data access audit logging and comprehensive key management—further assist organizations in meeting critical compliance requirements, ensuring that sensitive data remains protected at all times. Ultimately, implementing such robust encryption measures not only enhances security but also builds trust among stakeholders.

DataVantage provides a wide range of data management solutions that focus on the protection and governance of sensitive information in both mainframe and distributed settings. Among its key products are DataVantage for IMS, Db2, and VSAM, which incorporate sophisticated features for data masking, editing, and extraction, ensuring the safeguarding of Personally Identifiable Information (PII) during non-production activities. Furthermore, DataVantage DME (Data Masking Express) enables economical, real-time data masking for Db2, IMS, and VSAM environments, facilitating compliance without hindering existing operations. For distributed infrastructures, DataVantage Global offers comprehensive data masking, obfuscation, and de-identification processes, promoting both compliance and operational effectiveness across various platforms. Moreover, DataVantage Adviser streamlines the management of COBOL files following mainframe rehosting or application modernization, thereby improving data accessibility and editing capabilities. This holistic approach to data management not only enhances security measures but also supports organizations in their quest for regulatory compliance and operational integrity.

The increasing risks to security and the rise of stringent privacy laws have necessitated a more cautious approach to handling sensitive information. Oracle Data Masking and Subsetting offers database users a solution to enhance security, streamline compliance efforts, and lower IT expenses by sanitizing production data copies for use in testing, development, and various other functions, while also allowing for the removal of superfluous data. This tool allows for the extraction, obfuscation, and sharing of both full copies and subsets of application data with partners, whether they are within or outside the organization. By doing so, it ensures the database's integrity remains intact, thus supporting the ongoing functionality of applications. Additionally, Application Data Modeling automatically identifies columns within Oracle Database tables that contain sensitive data through established discovery patterns, including national IDs, credit card details, and other forms of personally identifiable information. Furthermore, it can recognize and map parent-child relationships that are defined within the database structure, enhancing the overall data management process.

We assist you in uncovering, generating, and customizing test data while also enabling you to visualize coverage and ensure data security, allowing you to concentrate on development tasks. Automate the generation of masked, tailored, and synthetic data to fulfill your development and testing requirements seamlessly. Quickly pinpoint sensitive data locations by implementing uniform masking across various databases. Enhance testers’ productivity by storing, expanding, sharing, and reusing test datasets effectively. Deliver smaller datasets to lessen infrastructure demands and enhance overall performance. Employ our extensive range of masking methods to ensure consistent data protection across all applications. Provide support for packaged applications to maintain solution integrity and accelerate deployment processes. Collaborate with risk, compliance, and audit teams to synchronize with data governance strategies. Boost test efficiency by utilizing dependable, trusted production data sets while simultaneously reducing server and storage demands with appropriately sized datasets for each team. This holistic approach not only streamlines the testing process but also fortifies the data management practices of your organization.

DPM easyData serves as an advanced engine for data de-identification and spoofing, offering methods such as masking, tokenization, anonymization, pseudonymization, and encryption to safeguard sensitive information. Through its data spoofing techniques, the software effectively substitutes entire data sets or fragments with non-sensitive alternatives, generating fictitious data that serves as a robust protective measure. This solution is tailored for web and application server environments, enabling databases to anonymize and tokenize information while enforcing masking policies for users without proper authorization when accessing sensitive materials. DPM easyData stands out for its precise control, allowing administrators to specify which users are permitted to access certain protection measures and outlining the actions they can perform under these policies. Furthermore, its highly customizable framework accommodates a wide variety of data types, offering unparalleled flexibility in defining input and token formats to meet diverse security needs. This adaptability ensures that organizations can maintain stringent data protection standards while managing sensitive information effectively.

The Mage™ Dynamic Data Masking module, part of the Mage data security platform, has been thoughtfully crafted with a focus on the needs of end customers. Developed in collaboration with clients, Mage™ Dynamic Data Masking effectively addresses their unique requirements and challenges. Consequently, this solution has advanced to accommodate virtually every potential use case that enterprises might encounter. Unlike many competing products that often stem from acquisitions or cater to niche scenarios, Mage™ Dynamic Data Masking is designed to provide comprehensive protection for sensitive data accessed by application and database users in production environments. Additionally, it integrates effortlessly into an organization’s existing IT infrastructure, eliminating the need for any substantial architectural modifications, thus ensuring a smoother transition for businesses implementing this solution. This strategic approach reflects a commitment to enhancing data security while prioritizing user experience and operational efficiency.

In today's fast-paced Agile DevOps environment, teams are increasingly required to enhance their speed and efficiency. BMC Compuware File-AID offers a versatile solution for file and data management across various platforms, allowing developers and QA personnel to swiftly and easily retrieve essential data and files without the need for exhaustive searches. This results in developers spending significantly less time on data management tasks and more time focused on creating new features and addressing production issues. By optimizing your test data, you can confidently implement code modifications without worrying about unforeseen effects. File-AID supports all standard file types, regardless of record length or format, facilitating seamless application integration. Additionally, it aids in comparing data files or objects, streamlining the process of validating test results. Users can also reformat existing files with ease, eliminating the need to start from the ground up. Furthermore, it supports the extraction and loading of relevant data subsets from various databases and files, enhancing overall productivity and effectiveness.

Mage™ offers comprehensive Static Data Masking (SDM) and Test Data Management (TDM) functionalities that are fully compatible with Imperva’s Data Security Fabric (DSF), ensuring robust safeguarding of sensitive or regulated information. This integration occurs smoothly within an organization’s current IT infrastructure and aligns with existing application development, testing, and data processes, all without necessitating any alterations to the existing architectural setup. As a result, organizations can enhance their data security while maintaining operational efficiency.

Subsalt represents a groundbreaking platform specifically designed to facilitate the utilization of anonymous data on a large enterprise scale. Its advanced Query Engine intelligently balances the necessary trade-offs between maintaining data privacy and ensuring fidelity to original data. The result of queries is fully-synthetic information that retains row-level granularity and adheres to original data formats, thereby avoiding any disruptive transformations. Additionally, Subsalt guarantees compliance through third-party audits, aligning with HIPAA's Expert Determination standard. It accommodates various deployment models tailored to the distinct privacy and security needs of each client, ensuring versatility. With certifications for SOC2-Type 2 and HIPAA compliance, Subsalt has been architected to significantly reduce the risk of real data exposure or breaches. Furthermore, its seamless integration with existing data and machine learning tools through a Postgres-compatible SQL interface simplifies the adoption process for new users, enhancing overall operational efficiency. This innovative approach positions Subsalt as a leader in the realm of data privacy and synthetic data generation.

IRI Data Masking as a Service is a professional services engagement to secure PII. Step 1: IRI agrees under NDA terms to classify, analyze, and report on the sensitive, at-risk data in your sources. We will discuss an initial cost estimate then hone it with you during data discovery. Step 2: Transfer the unprotected data to a secure on-premise or cloud-based staging area or provide remote, supervised access to IRI to the data sources(s) at issue. We'll use the tools in the award-winning IRI Data Protector suite to mask that data according to your business rules, on an ad hoc or recurring basis. Step 3: Our experts can also move newly-masked data to incremental replicas in production or to lower non-production environments. From either, the data is now safe for analytic initiatives, development, testing, or training. Tell us if you need additional services, like re-ID risk scoring (expert determination) of the de-identified data. This approach provides the benefits of proven data masking solution technology and services without the need to learn and customize new software from scratch. If you do want to use the software in-house, you will have everything pre-configured for easier long-term self-use and modification.

Safeguard your confidential SAP information by addressing security issues and adhering to data protection laws like the EU's General Data Protection Regulation (GDPR), South Africa's POPI Act, and California's Consumer Privacy Act of 2018 (CCPA) through the use of Data Secure™. In the current business landscape, ensuring data security has become paramount. Data Secure™, which is integrated within EPI-USE Labs' Data Sync Manager™ (DSM) suite, effectively tackles your data security concerns. This comprehensive solution features pre-set masking rules, allowing you to obfuscate any non-key field across various client-dependent SAP tables through diverse methods, including table look-up mappings, constant values, or even clearing a field entirely. Additionally, you can tailor these rules to suit your specific security requirements. By implementing Data Secure, your organization can comply with widely recognized data privacy standards and regulations, ensuring the protection of sensitive information in line with GDPR, Sarbanes Oxley, and the BDSG (Bundesdatenschutzgesetz). Ultimately, adopting such robust security measures not only enhances compliance but also fosters trust among your clients and stakeholders.

Complexity is the enemy of security. Simplify and scale fine-grained data access control. Dynamically authorize and audit every query to comply with data security and privacy regulations. Okera integrates seamlessly into your infrastructure – in the cloud, on premise, and with cloud-native and legacy tools. With Okera, data users can use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives.

DevOps can be simplified and privacy concerns eliminated by giving your teams full data autonomy via an easy-to use self-service portal. You can simplify access, remove data roadblocks, and speed up provisioning for data analysts, dev, testing, and other purposes. The Accelario Continuous DataOps platform is your one-stop-shop to all of your data needs. Eliminate DevOps bottlenecks, and give your teams high-quality, privacy-compliant information. The platform's four modules can be used as standalone solutions or as part of a comprehensive DataOps management platform. Existing data provisioning systems can't keep pace with agile requirements for continuous, independent access and privacy-compliant data in autonomous environments. With a single-stop-shop that provides comprehensive, high-quality, self-provisioning privacy compliant data, teams can meet agile requirements for frequent deliveries.

Privacy1 infrastructure brings transparency, safeguards GDPR | CCPA compliance, builds trust for your business. The solution shields your data centric organizations, lower data leak risks, ensures that no personal data is processed except with the right permission. The service has built in rich features you need to meet data compliance requirements and enforce your organizational data security to the highest level

The IRI Data Manager suite from IRI, The CoSort Company, provides all the tools you need to speed up data manipulation and movement. IRI CoSort handles big data processing tasks like DW ETL and BI/analytics. It also supports DB loads, sort/merge utility migrations (downsizing), and other data processing heavy lifts. IRI Fast Extract (FACT) is the only tool that you need to unload large databases quickly (VLDB) for DW ETL, reorg, and archival. IRI NextForm speeds up file and table migrations, and also supports data replication, data reformatting, and data federation. IRI RowGen generates referentially and structurally correct test data in files, tables, and reports, and also includes DB subsetting (and masking) capabilities for test environments. All of these products can be licensed standalone for perpetual use, share a common Eclipse job design IDE, and are also supported in IRI Voracity (data management platform) subscriptions.

Secure Multi-Data Archiving with a Single Interface OneVault archives email and all new data types that your organization uses today. Email, Instant Messaging and Teams, Zoom, Webex, and many other data types. OneVault gives you a single interface to archive from multiple systems. It is easy to organize consistent policies and support business continuity plans by centralizing important data in a secure cloud platform. e-Discovery is a single platform for managing and working with records. It is secure, transparent, and easy to use. OneVault combines the powerful features of our stand alone archiving solutions under one pane of glass. It is intuitive, secure, and scalable. Start with email and expand as new systems become available.

OpenText Data Express manages the test data environment. It improves test results, lowers testing costs, secures customer data against loss or misuse and enables accelerated delivery. Data Express automates generation of test data environments to reduce elapsed times by up to 80%. By masking sensitive data, test data retains the value for testing and keeps it safe from unauthorized uses. Data Express is a repository for test data knowledge. It provides a variety of management tools that allow test managers to control the generation of test data.

Qlik Gold Client enhances the management of test data in SAP settings by boosting efficiency, cutting costs, and ensuring security. This tool is specifically crafted to remove the need for development workarounds by allowing for the straightforward transfer of configuration, master, and transactional data subsets into testing environments. Users can swiftly define, duplicate, and synchronize transactional data from production systems to non-production targets. It also offers functionality to identify, select, and eliminate non-production data as required. The interface is designed to manage significant and complex data transformations with ease. Additionally, it automates the selection of data and facilitates effortless test data refresh cycles, thereby minimizing the time and effort invested in data management. One of the key features of Qlik Gold Client is its ability to safeguard personally identifiable information (PII) in non-production environments through effective data masking. This masking process utilizes a defined set of rules to "scramble" production data during its replication to non-production settings, thereby ensuring data privacy and compliance. Overall, Qlik Gold Client streamlines the testing process, making it more efficient and secure for organizations.

You have complete authority over the encryption of your information at all times, ensuring there are no hidden backdoors. One solution encompasses all systems. With the innovative template concept, the eperi® Gateway can be customized for all your cloud applications, aligning perfectly with your data protection needs. Your team can maintain their usual workflow as the eperi® Gateway seamlessly encrypts data, allowing essential application functionalities like searching and sorting to remain intact. This allows you to leverage the benefits of cloud applications while adhering to rigorous financial industry regulations, including privacy-preserving analytics. The rise of IoT introduces intelligent machines and products that autonomously gather data. With encryption, you can not only secure data privacy but also meet compliance standards effectively. By integrating such robust encryption measures, you can confidently navigate the complexities of data management in today’s digital landscape.

Maintain the essence, structure, and accuracy while ensuring confidentiality. Improve data security by anonymizing and altering sensitive information, as well as implementing pseudonymization strategies for adherence to privacy regulations and analytics purposes. The obscured data continues to hold its context and referential integrity, making it suitable for use in testing, analytics, or support scenarios. Serving as an exceptionally scalable and high-performing data masking solution, Informatica Persistent Data Masking protects sensitive information—like credit card details, addresses, and phone numbers—from accidental exposure by generating realistic, anonymized data that can be safely shared both internally and externally. Additionally, this solution minimizes the chances of data breaches in nonproduction settings, enhances the quality of test data, accelerates development processes, and guarantees compliance with various data-privacy laws and guidelines. Ultimately, adopting such robust data masking techniques not only protects sensitive information but also fosters trust and security within organizations.

BizDataX offers a data masking solution that delivers test data with the quality comparable to that of production environments. It ensures adherence to GDPR and various other regulations by concealing customer identities while supplying data for developers and testers. Utilizing masked or anonymized data rather than actual production data significantly mitigates associated risks. The focus is placed on managing policies, fulfilling business requirements, governing sensitive data, and adhering to diverse regulations. It also facilitates the monitoring of databases, data sources, and tables to identify the locations of sensitive information. Furthermore, it allows for the management of extensive customer databases and the seamless exchange of data with online partner retailers and delivery services. Given the stringent regulations surrounding medical records, compliance can be effectively maintained through the process of data anonymization, ensuring that patient information is protected. This capability not only safeguards sensitive data but also enhances the overall data management strategy for organizations.

Your IT department can implement advanced data masking techniques to restrict access to sensitive information, utilizing adaptable masking rules that correspond to the authentication levels of users. By incorporating mechanisms for blocking, auditing, and notifying users, IT staff, and external teams who interact with confidential data, the organization can maintain adherence to its security protocols as well as comply with relevant industry and legal privacy standards. Additionally, you can tailor data-masking strategies to meet varying regulatory or business needs, fostering a secure environment for personal and sensitive information. This approach not only safeguards data but also facilitates offshoring, outsourcing, and cloud-based projects. Furthermore, large datasets can be secured by applying dynamic masking to sensitive information within Hadoop environments, enhancing overall data protection. Such measures bolster the integrity of the organization's data security framework.

It can quickly generate data based on table names, column specifications, field sizes, data types, and other predefined constraints. These generators can easily be tailored to suit your specific needs. You can produce substantial amounts of data within just a few clicks in SQL Server Management Studio. The system allows for column-aware data generation, enabling the creation of data in one column that depends on the values in another. Users benefit from enhanced flexibility and manual oversight when crafting foreign key data. Custom generators that can be shared with your team are also available, allowing you to save regular expressions and SQL statement generators for collaborative use. Furthermore, you can write your own generators in Python, giving you the ability to create any additional data required. With seeded random data generation, you can ensure that the same dataset is produced consistently each time. Moreover, foreign key support helps maintain data consistency across various tables, making the process even more efficient and reliable. This versatility in data generation significantly streamlines workflows and enhances productivity for database management tasks.

IRI RowGen generates rows ... billions of rows of safe, intelligent test data in database, flat-file, and formatted report targets ... using metadata, not data. RowGen synthesizes and populates accurate, relational test data with the same characteristics of production data. RowGen uses the metadata you already have (or create on the fly) to randomly generate structurally and referentially correct test data, and/or randomly select data from real sets. RowGen lets you customize data formats, volumes, ranges, distributions, and other properties on the fly or with re-usable rules that support major goals like application testing and subsetting. RowGen uses the IRI CoSort engine to deliver the fastest generation, transformation, and bulk-load movement of big test data on the market. RowGen was designed by data modeling, integration, and processing experts to save time and energy in the creation of perfect, compliant test sets in production and custom formats. With RowGen, you can produce and provision safe, smart, synthetic test data for: DevOps, DB, DV, and DW prototypes, demonstrations, application stress-testing, and benchmarking -- all without needing production data.

Xeotek accelerates the development and exploration of data applications and streams for businesses through its robust desktop and web applications. The Xeotek KaDeck platform is crafted to cater to the needs of developers, operations teams, and business users equally. By providing a shared platform for business users, developers, and operations, KaDeck fosters a collaborative environment that minimizes misunderstandings, reduces the need for revisions, and enhances overall transparency for the entire team. With Xeotek KaDeck, you gain authoritative control over your data streams, allowing for significant time savings by obtaining insights at both the data and application levels during projects or routine tasks. Easily export, filter, transform, and manage your data streams in KaDeck, simplifying complex processes. The platform empowers users to execute JavaScript (NodeV4) code, create and modify test data, monitor and adjust consumer offsets, and oversee their streams or topics, along with Kafka Connect instances, schema registries, and access control lists, all from a single, user-friendly interface. This comprehensive approach not only streamlines workflow but also enhances productivity across various teams and projects.

High-quality test data plays a crucial role in enhancing both application development and testing processes, which is why top-tier development teams often insist on regularly populating their test environments with data sourced from production databases. Typically, a robust Test Data Management (TDM) strategy involves maintaining several full clones—usually between six to eight—of the production database to serve as test and development platforms. However, without the right automation tools, the process of provisioning test data becomes not only inefficient and labor-intensive but also poses significant risks, such as the potential exposure of sensitive information to unauthorized users, which can lead to compliance violations. The resource drain and challenges associated with data governance during the cloning process often result in test and development databases not being refreshed frequently enough, which can lead to unreliable test outcomes or outright test failures. Consequently, as defects are identified later in the development cycle, the overall costs associated with application development tend to rise, further complicating project timelines and resource allocation. Ultimately, addressing these issues is essential for maintaining both the integrity of the testing process and the overall efficiency of application development.

Datagen offers a self-service platform designed for creating synthetic data tailored specifically for visual AI applications, with an emphasis on both human and object data. This platform enables users to exert detailed control over the data generation process, facilitating the analysis of neural networks to identify the precise data required for enhancement. Users can effortlessly produce that targeted data to train their models effectively. To address various challenges in data generation, Datagen equips teams with a robust platform capable of producing high-quality, diverse synthetic data that is specific to particular domains. It also includes sophisticated features that allow for the simulation of dynamic humans and objects within their respective contexts. With Datagen, computer vision teams gain exceptional flexibility in managing visual results across a wide array of 3D environments, while also having the capability to establish distributions for every element of the data without any inherent biases, ensuring a fair representation in the generated datasets. This comprehensive approach empowers teams to innovate and refine their AI models with precision and efficiency.

Streamline the self-service provisioning and refreshing of enterprise workloads while seamlessly integrating with your current toolchain. Enable efficient data delivery and reutilization for data scientists via a comprehensive suite of APIs and automation tools. Achieve data recovery across any cloud environment from any moment in time, concurrently and at scale, surpassing traditional legacy solutions. Reduce the impact of ransomware and cyber threats by ensuring rapid recovery through immutable backup systems. A consolidated platform enhances the protection, security, retention, governance, and recovery of your data, whether on-premises or in the cloud. Actifio’s innovative software platform transforms isolated data silos into interconnected data pipelines. The Virtual Data Pipeline (VDP) provides comprehensive data management capabilities — adaptable for on-premises, hybrid, or multi-cloud setups, featuring extensive application integration, SLA-driven orchestration, flexible data movement, and robust data immutability and security measures. This holistic approach not only optimizes data handling but also empowers organizations to leverage their data assets more effectively.

You can forget about manual content classification or data entry. Doculayer.ai provides a configurable workflow that includes document processing services such as OCR, document type classification and topic classification, as well data extraction and masking. Doculayer.ai allows business users to take control of their learning and training by providing an intuitive user interface that makes labeling documents and data easy. Our hybrid data extraction approach allows machine learning models to be combined with patterns, rules, and library scripts to produce better results in less time. Data masking is an option to anonymize or pseudonymize sensitive data in documents. Doculayer.ai provides document intelligence to your Content Services Platform and Business Process Management systems. Your existing IT environment can be augmented for document processing by machine learning, natural language processing and computer vision technologies.

Envision extensive arrays of data entities, grasp their interconnections, and fine-tune associated data extractions to formulate ideal test datasets. Facilitate the comparison of files, even those located on different LPARs, thereby enhancing the capability to swiftly and routinely evaluate the repercussions of modifications. Streamline the intricate process of data management and test preparation by allowing developers and test engineers to execute data-related functions without the necessity of programming, scripting, SQL coding, or juggling multiple tools. Empower developers, test engineers, and analysts to achieve greater independence by allowing them to provision data as required, which lessens dependence on subject matter experts. Elevate application quality through improved testing scenarios, making the creation of comprehensive data extracts for testing more straightforward and enabling precise identification of the effects stemming from alterations in data components. By doing so, teams can respond more quickly to changes and enhance their overall productivity.

GxQuality™ is an automated quality assurance application that ensures thorough project validation by generating test scenarios and data while integrating with CI/CD and CV processes. This solution enhances traceability between test conditions and data, supported by managed services from both onshore and offshore teams. Our expertise encompasses a wide range of testing solutions across the enterprise, focusing on DevOps practices, continuous integration and delivery, computer vision, and effective release management strategies. With GxQuality™, organizations can achieve a seamless quality control process, ensuring that all aspects of software deliverables meet the highest standards.